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In this paper, a new method to have a safe place by human motion recognition and routing in an indoor environment, in presence of different objects, such as on a manufacturing shop floor, is presented. Due to the high cost and limitations of some of the available methods such as video surveillance, limitations in the indoor because of the presence of other objects, processing time, and limitation...
This paper presents a novel supervised clustering technique including different clustering algorithms which cooperate together to span the decision space in a supervised manner. It uses a variety of clustering methods for an efficient partitioning. An evolutionary algorithm is used to tune the key parameters of the cooperative scheme which minimizes an error-based objective function on the training...
This paper presents a novel method for moving object tracking in different scales. There are researches in tracking objects but most of them focus on specific subject and fail in some conditions such as changing position, moving camera, changing scale because of the distance variations. Camera movement is one of the most challenging events which causes to have a lot of fake moving objects in scenes...
This paper proposes a novel object detection approach based on local shape information. Boundary edge fragments preserve some features like shape and position which properly describe the outline of an object. Extraction of object boundary fragments is a challenging task in object detection. In this paper, a sophisticated system is proposed to achieve this goal. We propose local shape descriptors and...
Combination of 2D and 3D face recognition approaches intensifies recognition accuracy. In this paper, we propose a new algorithm for face recognition by applying hybrid approach, structural context and pyramidal shape index. Proposed pyramidal local shape index descriptors are extracted in each level or scale of the Gaussian pyramid of range image. In this way, we can extract high contrast and reliable...
In this paper, a palmprint identification and verification approach based on Pyramidal Histograms of Oriented Gradients (PHOG) and fast tree based matching is presented. In the feature extraction stage, proposed local histograms of oriented gradient are extracted in each level or scale of the Gaussian pyramid of the palmprint. This matter helps to extract high contrast and reliable lines. In the identification...
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